repo_id string | root string | num_frames int64 | num_episodes int64 | fps int64 | features dict | errors list | warnings list | strict_certificate_count int64 | certified_successes_per_task dict | sampled_frames int64 | black_image_samples int64 | non_finite_samples int64 | sample_tasks list | joint_names_expected list |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
visiobot/radeonvla-reflex-physical-2k | /workspace/RadeonVLA-Reflex/datasets/radeonvla_reflex_physical_2k | 468,889 | 2,000 | 20 | {
"observation.state": {
"dtype": "float32",
"shape": [
9
]
},
"action": {
"dtype": "float32",
"shape": [
9
]
},
"observation.images.world": {
"dtype": "video",
"shape": [
240,
320,
3
]
},
"observation.images.wrist": {
"dtype": "video",... | [] | [] | 2,000 | {
"apple_blue_left": 100,
"apple_blue_right": 100,
"apple_white_left": 100,
"apple_white_right": 100,
"banana_blue_left": 100,
"banana_blue_right": 100,
"banana_white_left": 100,
"banana_white_right": 100,
"lemon_blue_left": 100,
"lemon_blue_right": 100,
"lemon_white_left": 100,
"lemon_white_rig... | 1,000 | 0 | 0 | [
"Pick the apple and place it in the blue bowl on the left.",
"Pick the apple and place it in the blue bowl on the right.",
"Pick the apple and place it in the white bowl on the left.",
"Pick the apple and place it in the white bowl on the right.",
"Pick the banana and place it in the blue bowl on the left."... | [
"panda_joint1",
"panda_joint2",
"panda_joint3",
"panda_joint4",
"panda_joint5",
"panda_joint6",
"panda_joint7",
"panda_finger_joint1",
"panda_finger_joint2"
] |
RadeonVLA-Reflex Physical-2K
Physical-2K contains 2,000 strictly validated successful Genesis episodes for language-conditioned Franka fruit sorting. Coverage is exactly five fruits × four bowl positions × 100 episodes = 2,000 episodes.
Verified release facts
| Item | Value |
|---|---|
| Episodes | 2,000 |
| Frames | 468,889 |
| Registered task variations | 20 |
| Episodes per task variation | 100 |
| Control frequency | 20 Hz |
| Strict success certificates | 2,000 |
| Sampled image frames | 1,000 |
| Black sampled frames | 0 |
| Non-finite sampled frames | 0 |
| Validation errors / warnings | 0 / 0 |
The complete machine-readable report is available at
validation/dataset_validation.json (SHA256
fb1a1a0be5c8e5efa24342eeb62f962ae5a6b4b0e3465b83a86eb2460516e113).
Task coverage and language
The 20 task variations are the Cartesian product of:
- fruit: apple, banana, lemon, orange, plum;
- target: blue-left, blue-right, white-left, white-right.
Every task variation has exactly 100 successful episodes. The metadata contains
40 collected instruction strings because each task has two recorded language
forms, for example Pick the apple and place it in the blue bowl on the left.
and Sort the apple into the blue bowl on the left.
Observation and action schema
| Field | Shape/type | Description |
|---|---|---|
observation.images.world |
240×320 RGB video | World camera |
observation.images.wrist |
240×320 RGB video | Wrist camera |
observation.state |
9-D float32 | Franka arm and gripper qpos |
action |
9-D float32 | Absolute joint-position target |
Joint order is panda_joint1..7, panda_finger_joint1..2. Videos are AV1,
20 FPS, without audio. The dataset follows LeRobot codebase format v3.0.
Physical-success policy
The published manifest records strict_physics=true,
kinematic_grasp_assist=false, placement_nudge=false, and a rigid-body pose
write guard. Failed collection attempts were discarded. Each committed episode
has an atomic certificate under certificates/ and passed schema, coverage,
finite-value, image-statistics, intervention, and certificate correspondence
checks.
Physical-2K combines two independently audited 1K sources generated from source
commits dbc12b69e88be787b679bb41cf2026ca43e0eda6 and
cbf07f9306cd175e82d1e60d1c02cc0b07d2f9d2. The immutable aggregation details
remain in recording_manifest.json.
Limitations and license
This is simulation-only data for the registered fruit/bowl scene; it does not establish real-robot performance. The dataset is released under CC BY 4.0. YCB object assets retain their attribution requirements.
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